The project, “Understanding the Annotation Process: Annotation for Big Data”, aims to investigate how we can efficiently and with the least effort create training sets which can be used by automatic techniques to learn from. The project has three main research questions:
– How do human assessors judge and assess text documents, images, and videos?
– What are the main factors which affect assessor performance (e.g. accuracy, speed, etc.)?
– What material is most easy for human assessors to judge, and which will also give the best “bang for the buck” when used as input to a machine learning system?

BUFVC will provide a data set, from the Roundabout collection (courtesy of the BFI) to facilitate research into the moving image aspect of the project.